Here we present a method of genome-wide inferred study (GWIS) that provides an approximation of genome-wide association study (GWAS) summary statistics for a variable that is a function of phenotypes ...for which GWAS summary statistics, phenotypic means, and covariances are available. A GWIS can be performed regardless of sample overlap between the GWAS of the phenotypes on which the function depends. Because a GWIS provides association estimates and their standard errors for each SNP, a GWIS can form the basis for polygenic risk scoring, LD score regression, Mendelian randomization studies, biological annotation, and other analyses. GWISs can also be used to boost power of a GWAS meta-analysis where cohorts have not measured all constituent phenotypes in the function. We demonstrate the accuracy of a BMI GWIS by performing power simulations and type I error simulations under varying circumstances, and we apply a GWIS by reconstructing a body mass index (BMI) GWAS based on a weight GWAS and a height GWAS. Furthermore, we apply a GWIS to further our understanding of the underlying genetic structure of bipolar disorder and schizophrenia and their relation to educational attainment. Our analyses suggest that the previously reported genetic correlation between schizophrenia and educational attainment is probably induced by the observed genetic correlation between schizophrenia and bipolar disorder and the previously reported genetic correlation between bipolar disorder and educational attainment.
There are substantial differences, or variation, between humans in aggression, with its molecular genetic basis mostly unknown. This review summarizes knowledge on the genetic contribution to ...variation in aggression with the following three foci(1) a comprehensive overview of reviews on the genetics of human aggression, (2) a systematic review of genome-wide association studies (GWASs), and (3) an automated tool for the selection of literature based on supervised machine learning. The phenotype definition ‘aggression’ (or ‘aggressive behaviour’, or ‘aggression-related traits’) included anger, antisocial behaviour, conduct disorder, and oppositional defiant disorder. The literature search was performed in multiple databases, manually and using a novel automated selection tool, resulting in 18 reviews and 17 GWASs of aggression. Heritability estimates of aggression in children and adults are around 50%, with relatively small fluctuations around this estimate. In 17 GWASs, 817 variants were reported as suggestive (P ≤ 1.0E), including 10 significant associations (P ≤ 5.0E). Nominal associations (P ≤ 1E) were found in gene-based tests for genes involved in immune, endocrine, and nervous systems. Associations were not replicated across GWASs. A complete list of variants and their position in genes and chromosomes are available online. The automated literature search tool produced literature not found by regular search strategies. Aggression in humans is heritable, but its genetic basis remains to be uncovered. No sufficiently large GWASs have been carried out yet. With increases in sample size, we expect aggression to behave like other complex human traits for which GWAS has been successful.
The evolving field of multi‐omics combines data and provides methods for simultaneous analysis across several omics levels. Here, we integrated genomics (transmitted and non‐transmitted polygenic ...scores PGSs), epigenomics, and metabolomics data in a multi‐omics framework to identify biomarkers for Attention‐Deficit/Hyperactivity Disorder (ADHD) and investigated the connections among the three omics levels. We first trained single‐ and next multi‐omics models to differentiate between cases and controls in 596 twins (cases = 14.8%) from the Netherlands Twin Register (NTR) demonstrating reasonable in‐sample prediction through cross‐validation. The multi‐omics model selected 30 PGSs, 143 CpGs, and 90 metabolites. We confirmed previous associations of ADHD with glucocorticoid exposure and the transmembrane protein family TMEM, show that the DNA methylation of the MAD1L1 gene associated with ADHD has a relation with parental smoking behavior, and present novel findings including associations between indirect genetic effects and CpGs of the STAP2 gene. However, out‐of‐sample prediction in NTR participants (N = 258, cases = 14.3%) and in a clinical sample (N = 145, cases = 51%) did not perform well (range misclassification was 0.40, 0.57). The results highlighted connections between omics levels, with the strongest connections between non‐transmitted PGSs, CpGs, and amino acid levels and show that multi‐omics designs considering interrelated omics levels can help unravel the complex biology underlying ADHD.
Abstract
Telomeres are repetitive DNA sequences located at the end of chromosomes, which are associated to biological aging, cardiovascular disease, cancer and mortality. Lipid and fatty acid ...metabolism have been associated with telomere shortening. We have conducted an in-depth study investigating the association of metabolic biomarkers with telomere length (LTL). We performed an association analysis of 226 metabolic biomarkers with LTL using data from 11 775 individuals from six independent population-based cohorts (BBMRI-NL consortium). Metabolic biomarkers include lipoprotein lipids and subclasses, fatty acids, amino acids, glycolysis measures and ketone bodies. LTL was measured by quantitative polymerase chain reaction or FlowFISH. Linear regression analysis was performed adjusting for age, sex, lipid-lowering medication and cohort-specific covariates (model 1) and additionally for body mass index (BMI) and smoking (model 2), followed by inverse variance-weighted meta-analyses (significance threshold Pmeta = 6.5 × 10−4). We identified four metabolic biomarkers positively associated with LTL, including two cholesterol to lipid ratios in small VLDL (S-VLDL-C % and S-VLDL-CE %) and two omega-6 fatty acid ratios (FAw6/FA and LA/FA). After additionally adjusting for BMI and smoking, these metabolic biomarkers remained associated with LTL with similar effect estimates. In addition, cholesterol esters in very small VLDL (XS-VLDL-CE) became significantly associated with LTL (P = 3.6 × 10−4). We replicated the association of FAw6/FA with LTL in an independent dataset of 7845 individuals (P = 1.9 × 10−4). To conclude, we identified multiple metabolic biomarkers involved in lipid and fatty acid metabolism that may be involved in LTL biology. Longitudinal studies are needed to exclude reversed causation.
The stability of colloidal dispersions can be severely affected by the presence of surfactants. Because surfactants can adsorb at colloidal surfaces as well as form micelles, one can expect an ...interplay between both phenomena. Using grand-canonical coarse-grained Monte Carlo simulations on surfactant solutions confined between two surfaces, we investigate how adsorption and micelle formation affects the effective interaction between two colloidal particles, and hence, the stability of the colloidal dispersion. For solvophilic colloidal surfaces, we observe a short-ranged oscillatory solvation pressure that is hardly affected by the presence of surfactants in the system. The effective surface-surface interaction, however, reveals a decrease in solvophilic stabilization as a function of surfactant chemical potential. For solvophobic surfaces, we find that the capillary evaporation observed in a confined pure solvent, is counteracted by the addition of surfactants. Around the critical micelle concentration (CMC), the surface-surface interaction even becomes repulsive, enhancing stabilization of the colloidal dispersion. In contrast, the formation of micelles at concentrations above the CMC causes an additional depletion effect, resulting in an effective attraction, which in turn can destabilize a colloidal dispersion.
Snapshots of confined solvent/surfactant simulations: a system with solvophobic surfaces (left) and one with solvophilic surfaces (right). Solvophilic head groups in white, solvophobic tails in dark-grey, solvents not shown.
To assess whether two proteins will interact under physiological conditions, information on the interaction free energy is needed. Statistical learning techniques and docking methods for predicting ...protein-protein interactions cannot quantitatively estimate binding free energies. Full atomistic molecular simulation methods do have this potential, but are completely unfeasible for large-scale applications in terms of computational cost required. Here we investigate whether applying coarse-grained (CG) molecular dynamics simulations is a viable alternative for complexes of known structure.
We calculate the free energy barrier with respect to the bound state based on molecular dynamics simulations using both a full atomistic and a CG force field for the TCR-pMHC complex and the MP1-p14 scaffolding complex. We find that the free energy barriers from the CG simulations are of similar accuracy as those from the full atomistic ones, while achieving a speedup of >500-fold. We also observe that extensive sampling is extremely important to obtain accurate free energy barriers, which is only within reach for the CG models. Finally, we show that the CG model preserves biological relevance of the interactions: (i) we observe a strong correlation between evolutionary likelihood of mutations and the impact on the free energy barrier with respect to the bound state; and (ii) we confirm the dominant role of the interface core in these interactions. Therefore, our results suggest that CG molecular simulations can realistically be used for the accurate prediction of protein-protein interaction strength.
The python analysis framework and data files are available for download at http://www.ibi.vu.nl/downloads/bioinformatics-2013-btt675.tgz.
We show that epigenome- and transcriptome-wide association studies (EWAS and TWAS) are prone to significant inflation and bias of test statistics, an unrecognized phenomenon introducing spurious ...findings if left unaddressed. Neither GWAS-based methodology nor state-of-the-art confounder adjustment methods completely remove bias and inflation. We propose a Bayesian method to control bias and inflation in EWAS and TWAS based on estimation of the empirical null distribution. Using simulations and real data, we demonstrate that our method maximizes power while properly controlling the false positive rate. We illustrate the utility of our method in large-scale EWAS and TWAS meta-analyses of age and smoking.
OBJECTIVETo identify a plasma metabolomic biomarker signature for migraine.
METHODSPlasma samples from 8 Dutch cohorts (n = 10,1532,800 migraine patients and 7,353 controls) were profiled on a ...H-NMR-based metabolomics platform, to quantify 146 individual metabolites (e.g., lipids, fatty acids, and lipoproteins) and 79 metabolite ratios. Metabolite measures associated with migraine were obtained after single-metabolite logistic regression combined with a random-effects meta-analysis performed in a nonstratified and sex-stratified manner. Next, a global test analysis was performed to identify sets of related metabolites associated with migraine. The Holm procedure was applied to control the family-wise error rate at 5% in single-metabolite and global test analyses.
RESULTSDecreases in the level of apolipoprotein A1 (β −0.10; 95% confidence interval CI −0.16, −0.05; adjusted p = 0.029) and free cholesterol to total lipid ratio present in small high-density lipoprotein subspecies (HDL) (β −0.10; 95% CI −0.15, −0.05; adjusted p = 0.029) were associated with migraine status. In addition, only in male participants, a decreased level of omega-3 fatty acids (β −0.24; 95% CI −0.36, −0.12; adjusted p = 0.033) was associated with migraine. Global test analysis further supported that HDL traits (but not other lipoproteins) were associated with migraine status.
CONCLUSIONSMetabolic profiling of plasma yielded alterations in HDL metabolism in migraine patients and decreased omega-3 fatty acids only in male migraineurs.
We report molecular simulations suggesting that the kinetics of surfactant micelle formation can be sped up significantly by a replication mechanism, in which growing micelles become unstable and ...split into two similar sized micelles. We argue that for certain surfactants types around the critical micelle concentration, such a mechanism becomes more dominant than the commonly accepted nucleation pathway.
PDF
